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Author |
Jose Manuel Alvarez; Antonio Lopez; Ramon Baldrich |
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Title |
Shadow Resistant Road Segmentation from a Mobile Monocular System |
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2007 |
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3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:9–16 |
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road detection |
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Gerona (Spain) |
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ADAS;CIC |
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no |
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ADAS @ adas @ ALB2007 |
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943 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
Real Time on Board Stereo Camera Pose through Image Registration |
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Conference Article |
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2008 |
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IEEE Intelligent Vehicles Symposium, |
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804–809 |
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Eindhoven (Netherlands) |
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ADAS |
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no |
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ADAS @ adas @ DoS2008a |
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1015 |
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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat |
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Title |
Photometric Stereo through and Adapted Alternation Approach |
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Conference Article |
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Year |
2008 |
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IEEE International Conference on Image Processing, |
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1500–1503 |
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San Diego; CA; USA |
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ADAS |
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ADAS @ adas @ JSL2008d |
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1016 |
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Author |
Angel Sappa; Fadi Dornaika; David Geronimo; Antonio Lopez |
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Title |
Registration-based Moving Object Detection from a Moving Camera |
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Conference Article |
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Year |
2008 |
Publication |
IROS2008 2nd Workshop on Perception, Planning and Navigation for Intelligent Vehicles |
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65–69 |
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This paper presents a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three stages. Initially, feature points are extracted and tracked through consecutive frames. Then, a RANSAC based approach is used for registering
two 3D point sets with known correspondences by means of the quaternion method. Finally, the computed 3D rigid displacement is used to map two consecutive frames into the same coordinate system. Moving objects correspond to those areas with large registration errors. Experimental results, in different scenarios, show the viability of the proposed approach. |
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Nice (France) |
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ADAS |
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no |
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ADAS @ adas @ SDG2008 |
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1017 |
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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
An Adapted Alternation Approach for Recommender Systems |
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Conference Article |
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Year |
2008 |
Publication |
IEEE International Conference on e–Business Engineering, |
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128–135 |
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This paper presents an adaptation of the alternation technique to tackle the prediction task in recommender systems. These systems are widely considered in electronic commerce to help customers to find products they will probably like or dislike. As the SVD-based approaches, the proposed adapted alternation technique uses all the information stored in the system to find the predictions. The main advantage of this technique with respect to the SVD-based ones is that it can deal with missing data. Furthermore, it has a smaller computational cost. Experimental results with public data sets are provided in order to show the viability of the proposed adapted alternation approach. |
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Xi’an (Xina) |
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ADAS |
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ADAS @ adas @ JSL2008e |
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1044 |
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Author |
Jose Manuel Alvarez; Antonio Lopez; Ramon Baldrich |
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Title |
Illuminant Invariant Model-Based Road Segmentation |
Type |
Conference Article |
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Year |
2008 |
Publication |
IEEE Intelligent Vehicles Symposium, |
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Pages |
1155–1180 |
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Keywords |
road detection |
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Address |
Eindhoven (The Netherlands) |
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ADAS;CIC |
Approved |
no |
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Call Number |
ADAS @ adas @ ALB2008 |
Serial |
1045 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
Improving Appearance-Based 3D Face Tracking Using Sparse Stereo Data |
Type |
Conference Article |
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Year |
2007 |
Publication |
Advances in Computer Graphics and Computer Vision, |
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354–366 |
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Springer Verlag |
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J. Braz, A. Ranchordas, H. Araujo and J. Jorge, |
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VISAPP |
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ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ DoS2007d |
Serial |
1046 |
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Permanent link to this record |
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Author |
Jose Manuel Alvarez; Antonio Lopez |
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Title |
Novel Index for Objective Evaluation of Road Detection Algorithms |
Type |
Conference Article |
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Year |
2008 |
Publication |
Intelligent Transportation Systems. 11th International IEEE Conference on, |
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Pages |
815–820 |
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road detection |
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Address |
Beijing (Xina) |
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ITSC |
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ADAS |
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no |
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ADAS @ adas @ AlL2008 |
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1074 |
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Author |
Arnau Ramisa; Adriana Tapus; Ramon Lopez de Mantaras; Ricardo Toledo |
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Title |
Mobile Robot Localization using Panoramic Vision and Combination of Feature Region Detectors |
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Conference Article |
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Year |
2008 |
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IEEE International Conference on Robotics and Automation, |
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538–543 |
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Pasadena; CA; USA |
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ICRA |
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RV;ADAS |
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no |
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Admin @ si @ RTL2008 |
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1144 |
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Permanent link to this record |
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Author |
Jose Manuel Alvarez; Theo Gevers; Antonio Lopez |
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Title |
Learning Photometric Invariance from Diversified Color Model Ensembles |
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Conference Article |
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Year |
2009 |
Publication |
22nd IEEE Conference on Computer Vision and Pattern Recognition |
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565–572 |
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road detection |
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Abstract |
Color is a powerful visual cue for many computer vision applications such as image segmentation and object recognition. However, most of the existing color models depend on the imaging conditions affecting negatively the performance of the task at hand. Often, a reflection model (e.g., Lambertian or dichromatic reflectance) is used to derive color invariant models. However, those reflection models might be too restricted to model real-world scenes in which different reflectance mechanisms may hold simultaneously. Therefore, in this paper, we aim to derive color invariance by learning from color models to obtain diversified color invariant ensembles. First, a photometrical orthogonal and non-redundant color model set is taken on input composed of both color variants and invariants. Then, the proposed method combines and weights these color models to arrive at a diversified color ensemble yielding a proper balance between invariance (repeatability) and discriminative power (distinctiveness). To achieve this, the fusion method uses a multi-view approach to minimize the estimation error. In this way, the method is robust to data uncertainty and produces properly diversified color invariant ensembles. Experiments are conducted on three different image datasets to validate the method. From the theoretical and experimental results, it is concluded that the method is robust against severe variations in imaging conditions. The method is not restricted to a certain reflection model or parameter tuning. Further, the method outperforms state-of- the-art detection techniques in the field of object, skin and road recognition. |
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Miami (USA) |
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1063-6919 |
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978-1-4244-3992-8 |
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CVPR |
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ADAS;ISE |
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ADAS @ adas @ AGL2009 |
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1169 |
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